Make.com vs Microsoft Semantic Kernel
Detailed side-by-side comparison to help you choose the right tool
Make.com
🟢No CodeAutomation & Workflows
Make.com: Visual automation platform with AI integration and workflow orchestration
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Starting Price
FreeMicrosoft Semantic Kernel
🔴DeveloperAI Development Platforms
SDK for integrating cutting-edge LLM technology into applications, with support for building AI agents and connecting model capabilities into existing app workflows.
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Starting Price
FreeFeature Comparison
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💡 Our Take
Choose Make.com if your priority is fast automation across marketing, sales, support, finance, and IT systems with pricing starting at $0 and paid plans from $12/month. Choose Semantic Kernel if you are a developer team building AI features inside a larger software product, especially in Microsoft-oriented engineering environments.
Make.com - Pros & Cons
Pros
- ✓Visual scenario builder supports routers, filters, scheduled runs, subscenarios, real-time execution monitoring, and reusable scenario templates.
- ✓Large connector ecosystem with 3,000+ standard apps, 350+ AI apps, and 300+ Make API endpoints for custom automation work.
- ✓Free plan includes 1,000 credits/month, 2 active scenarios, 3,000+ apps, routers and filters, and customer support with no time limit.
- ✓Paid plans support unlimited active scenarios, 1-minute scheduling, higher data transfer limits, and access to the Make API starting at $12/month for 10,000 credits.
- ✓Enterprise options include SSO, domain claim, on-prem agents for local systems such as SAP, advanced security features, 24/7 Enterprise support, and overage protection.
- ✓Make is used by 400,000+ customers across 200+ countries and territories, backed by a team of 350+ employees and parent company Celonis.
Cons
- ✗Credit-based billing can become hard to forecast because each module action in a scenario consumes credits.
- ✗The Free plan is limited to 1,000 credits/month, 2 active scenarios, 15-minute minimum scheduling, 5-minute maximum execution time, and 5 MB file processing.
- ✗Native AI features are useful for orchestration, but Make is not a full model development, vector database, or dedicated RAG platform.
- ✗Advanced governance and security features such as SSO, domain claim, audit logs, 24/7 support, and on-prem agents are Enterprise-oriented.
- ✗Complex scenarios still require careful technical design, especially when handling retries, data transformation, API limits, and high-volume AI calls.
Microsoft Semantic Kernel - Pros & Cons
Pros
- ✓Microsoft-backed open-source project with a public GitHub repository and official Microsoft Learn documentation.
- ✓Designed for embedding LLM capabilities directly into applications rather than forcing teams into a separate hosted workflow tool.
- ✓Supports developer-oriented agent and plugin patterns, making it suitable for connecting AI behavior to existing software functions and business systems.
- ✓Relevant to both C# and Python teams, which is useful for organizations with Microsoft/.NET systems as well as modern AI engineering stacks.
- ✓Better suited to production software engineering workflows than many no-code agent tools because it is an SDK that can be versioned, tested, and integrated into existing codebases.
- ✓Useful for teams that want structured orchestration around model calls instead of one-off prompt/API integrations.
Cons
- ✗Requires software engineering work; it is not a ready-made AI agent product for non-technical users.
- ✗The SDK itself does not eliminate model, hosting, monitoring, security, or infrastructure costs for production deployments.
- ✗Teams still need to design agent behavior, plugins, guardrails, and application-specific integrations themselves.
- ✗May be more framework than necessary for simple chatbot or single-prompt use cases.
- ✗The provided website content does not show specific hosted pricing tiers, SLAs, or managed-service guarantees for Semantic Kernel itself.
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